Ioannis Melas, Data Scientist and Machine Learning Developer in Cambridge, United Kingdom
Ioannis Melas

Data Scientist and Machine Learning Developer in Cambridge, United Kingdom

Member since January 19, 2020
Ioannis is a data scientist with expertise in prototyping, developing, and deploying data science and ML workflows that best leverage business data. This includes exploratory analysis such as dimensionality reduction, clustering, feature extraction, model fit/parameter estimation, and supervised analysis such as classification, regression. His expertise includes both structured and unstructured data (NLP). Notable clients include the U.S. Food & Drug Administration and AstraZeneca.
Ioannis is now available for hire

Portfolio

  • AstraZeneca
    Python 3, Bash Script, Data Science, Machine Learning...
  • Arm
    Python 3, Scikit-learn, Keras, TensorFlow...
  • UCB Celltech
    R, Python 3, Spotfire, Linux, H20, Keras, LSTM, Git, Python, Data Analysis...

Experience

Location

Cambridge, United Kingdom

Availability

Part-time

Preferred Environment

Linux, Python 3, Flask-RESTful, Streamlit, Spotfire, Python, R, Bash

The most amazing...

...NLP solution I've developed was for the text summarization and classification of biomedical literature routinely used by research scientists.

Employment

  • Data Science Contractor

    2020 - PRESENT
    AstraZeneca
    • Developed a machine learning workflow to leverage and interpret genetic data. This included parsing and preprocessing of patient data, normalization, dimensionality reduction, statistical tests, and supervised analysis.
    • Created a natural language solution for mining biomedical literature. The data was structured in an Elasticsearch database, cleaned, tokenized using the Natural Language Toolkit (NLTK), vectorized, and then used in a text classification framework.
    • Built dashboards and UI using Streamlit in Python. Deployed using Nginx.
    Technologies: Python 3, Bash Script, Data Science, Machine Learning, Natural Language Processing (NLP), Scikit-learn, Keras, TensorFlow, Streamlit, Nginx, Python, Data Analysis, Spotfire, Flask, Git
  • Data Science Contractor

    2019 - 2020
    Arm
    • Developed a machine learning framework for maximizing coverage in CPU verification. Development was in Python and deployed on HPC using Slurm Workload Manager.
    • Developed workflows leveraging adversarial learning using GANs and programmed in Python Keras.
    • Addressed numerical optimization problems using genetic algorithms with custom GA implementation.
    Technologies: Python 3, Scikit-learn, Keras, TensorFlow, Generative Adversarial Networks (GANs), Bash, Jenkins, Git, Slurm, GitHub, Python, Deep Learning, Genetic Algorithms, Numerical Methods, Convex Optimization
  • Principal Data Scientist

    2016 - 2019
    UCB Celltech
    • Built machine learning workflows to predict patient response to candidate drugs. Developed in R.
    • Led a team of three developers to create exploratory analytics solutions/dashboards to visualize high dimensional data. Results were pre-calculated in R, then imported in TIBCO Spotfire.
    • Designed machine learning solutions to predict drug activity in assays. Used LSTMs to model chemical structures as free text, and applied methods from text classification.
    Technologies: R, Python 3, Spotfire, Linux, H20, Keras, LSTM, Git, Python, Data Analysis, Data Analytics, Data Science, Machine Learning, Bioinformatics, Genomics
  • Postdoctoral Research Fellow

    2014 - 2016
    U.S. Food & Drug Administration
    • Developed a solution for predicting drug adverse events based on their transcriptomic profiles.
    • Created a linear programming formulation to model the structure of directed graphs.
    • Applied a solution to predict the adverse effects of new compounds.
    Technologies: R, Linux, C, Slurm, Linear Optimization, NetworkX, Bioinformatics, Genomics, Drug Development, Python, Data Science, Data Analytics

Experience

  • Mine Biomedical Literature Using Elasticsearch and NLP

    Parsed and created a local copy of Pubmed, indexed using Elasticsearch, and created a UI using Streamlit to allow the user to query the whole of Pubmed, pull the papers that match their query, and perform basic NLP tasks using NLTK and Spacy.

  • Framework for CPU Verification

    Developed a machine learning framework for maximizing coverage in CPU verification. I leveraged adversarial learning using GANs and programmed in Python Keras. It was deployed using a command line API and is now routinely used in new products.

  • Method for Predicting Efficacy of New Drugs

    Developed machine learning workflows to predict patient response to candidate drugs. I integrated several data sources including free text datasets to built drug profiles, which I then used in a classification framework to predict their efficacy on patients. Developed in R. Results were ported to Spotfire for visualization.

Skills

  • Languages

    Bash, Bash Script, Python, R, C
  • Libraries/APIs

    Scikit-learn, Keras, TensorFlow, LSTM, NLTK, Flask-RESTful, SpaCy, NetworkX
  • Paradigms

    Data Science
  • Industry Expertise

    Bioinformatics
  • Other

    Machine Learning, Mathematical Models, Linear Optimization, Genomics, Numerical Methods, Numerical Simulations, Numerical Modeling, Streamlit, Natural Language Processing (NLP), Slurm, Data Analysis, Mixed-integer Linear Programming, Convex Optimization, Mechanics, Engineering, Generative Adversarial Networks (GANs), Fluid Dynamics, Computational Physics, Deep Learning, Genetic Algorithms, Data Analytics, Drug Development, Gunicorn
  • Tools

    Spotfire, Git, Nginx, Jenkins, MATLAB, GitHub
  • Platforms

    Linux, H20
  • Frameworks

    Flask
  • Storage

    Elasticsearch

Education

  • Ph.D. in Numerical Optimization, Machine Learning, Bioinformatics
    2008 - 2013
    National Technical University of Athens - Athens, Greece
  • Master's Degree in Mechanical Engineering
    2003 - 2008
    National Technical University of Athens - Athens, Greece

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